This is a presentation¶

     B cell progenitor        CD14+ Monocytes        CD16+ Monocytes 
                   522                   3369                    461 
            CD4 Memory              CD4 Naive           CD8 effector 
                  2227                   1952                    755 
             CD8 Naive         Dendritic cell Double negative T cell 
                  1297                    133                    147 
               NK cell                    pDC              Platelets 
                   477                    114                      2 
            pre-B cell 
                   453 
CD14+ Monocytes CD16+ Monocytes        Lymphoid       Platelets 
           3369             461            8077               2 
     B cell progenitor        CD14+ Monocytes        CD16+ Monocytes 
                   636                   4032                    506 
            CD4 Memory              CD4 Naive           CD8 effector 
                  1999                   1549                    747 
             CD8 Naive         Dendritic cell Double negative T cell 
                  1069                    131                    138 
               NK cell                    pDC              Platelets 
                   458                    126                      5 
            pre-B cell 
                   620 
CD14+ Monocytes CD16+ Monocytes        Lymphoid       Platelets 
           4032             506            7473               5 
Scale for 'y' is already present. Adding another scale for 'y', which will
replace the existing scale.

Scale for 'y' is already present. Adding another scale for 'y', which will
replace the existing scale.

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

UMAP embedding was not computed. Running run_umap()...

Warning message:
"The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session"
Warning message:
"Using `as.character()` on a quosure is deprecated as of rlang 0.3.0.
Please use `as_label()` or `as_name()` instead.
This warning is displayed once per session."
Error in eval(expr, envir, enclos): object 'gsea.positive' not found
Traceback:
Intersecting features names in the model and the gene set annotation results in a total of 7281 features.


Running feature set Enrichment Analysis with the following options...
View: ATAC_distal 
Number of feature sets: 633 
Set statistic: mean.diff 
Statistical test: parametric 


Subsetting weights with positive sign




Intersecting features names in the model and the gene set annotation results in a total of 7281 features.


Running feature set Enrichment Analysis with the following options...
View: ATAC_distal 
Number of feature sets: 633 
Set statistic: mean.diff 
Statistical test: parametric 


Subsetting weights with negative sign




Registered S3 method overwritten by 'spatstat':
  method     from
  print.boxx cli 

Warning message in get0(oNam, envir = ns):
“internal error -3 in R_decompress1”
Error: .onLoad failed in loadNamespace() for 'checkmate', details:
  call: get0(oNam, envir = ns)
  error: lazy-load database '/usr/local/lib/R/site-library/backports/R/backports.rdb' is corrupt
Traceback:

1. Signac::RunChromVAR
2. getExportedValue(pkg, name)
3. asNamespace(ns)
4. getNamespace(ns)
5. loadNamespace(name)
6. namespaceImportFrom(ns, loadNamespace(j <- i[[1L]], c(lib.loc, 
 .     .libPaths()), versionCheck = vI[[j]]), i[[2L]], from = package)
7. asNamespace(ns)
8. loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
9. namespaceImportFrom(ns, loadNamespace(j <- i[[1L]], c(lib.loc, 
 .     .libPaths()), versionCheck = vI[[j]]), i[[2L]], from = package)
10. asNamespace(ns)
11. loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
12. namespaceImportFrom(ns, loadNamespace(j <- i[[1L]], c(lib.loc, 
  .     .libPaths()), versionCheck = vI[[j]]), i[[2L]], from = package)
13. asNamespace(ns)
14. loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]])
15. namespaceImport(ns, loadNamespace(i, c(lib.loc, .libPaths()), 
  .     versionCheck = vI[[i]]), from = package)
16. loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]])
17. runHook(".onLoad", env, package.lib, package)
18. stop(gettextf("%s failed in %s() for '%s', details:\n  call: %s\n  error: %s", 
  .     hookname, "loadNamespace", pkgname, deparse(conditionCall(res))[1L], 
  .     conditionMessage(res)), call. = FALSE, domain = NA)
Bioconductor version 3.12 (BiocManager 1.30.10), R 4.0.3 (2020-10-10)

Installing github package(s) 'GreenleafLab/chromVAR'

Downloading GitHub repo GreenleafLab/chromVAR@HEAD

BiocParallel (1.24.0 -> 1.24.1) [CRAN]
R6           (2.4.1  -> 2.5.0 ) [CRAN]
digest       (0.6.25 -> 0.6.27) [CRAN]
generics     (0.0.2  -> 0.1.0 ) [CRAN]
cpp11        (0.2.3  -> 0.2.4 ) [CRAN]
backports    (1.1.10 -> 1.2.0 ) [CRAN]
diffobj      (NA     -> 0.3.2 ) [CRAN]
rstudioapi   (0.11   -> 0.12  ) [CRAN]
waldo        (NA     -> 0.2.3 ) [CRAN]
brio         (NA     -> 1.1.0 ) [CRAN]
colorspace   (1.4-1  -> 2.0-0 ) [CRAN]
labeling     (0.3    -> 0.4.2 ) [CRAN]
testthat     (2.3.2  -> 3.0.0 ) [CRAN]
nabor        (NA     -> 0.5.0 ) [CRAN]
Installing 14 packages: BiocParallel, R6, digest, generics, cpp11, backports, diffobj, rstudioapi, waldo, brio, colorspace, labeling, testthat, nabor

✔  checking for file ‘/tmp/Rtmptd3t2X/remotesa7225dce/GreenleafLab-chromVAR-0f27fcc/DESCRIPTION’
─  preparing ‘chromVAR’:
✔  checking DESCRIPTION meta-information
─  cleaning src
─  checking for LF line-endings in source and make files and shell scripts
─  checking for empty or unneeded directories
─  building ‘chromVAR_1.5.0.tar.gz’
   

Installation path not writeable, unable to update packages: codetools,
  KernSmooth, nlme

Old packages: 'chromVAR', 'deldir', 'HDF5Array', 'leiden', 'MOFA2',
  'patchwork', 'reticulate', 'rhdf5', 'Rhdf5lib', 'Signac', 'xfun'

Warning message in FetchData(object = object, vars = c(dims, "ident", features), :
"The following requested variables were not found: MA1636.1, MA0102.4, MA0523.1, MA0768.1"
Error: None of the requested features were found: MA1636.1, MA0102.4, MA0523.1, MA0768.1 in slot data
Traceback:

1. FeaturePlot(sortedSeurat, features = motifs.to.plot, reduction = "umap", 
 .     combine = TRUE)
2. stop("None of the requested features were found: ", paste(features, 
 .     collapse = ", "), " in slot ", slot, call. = FALSE)
R version 4.0.3 (2020-10-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux bullseye/sid

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.10.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] psych_2.0.9         magrittr_1.5        ggbio_1.38.0       
 [4] BiocGenerics_0.36.0 msigdbr_7.2.1       ggpubr_0.4.0       
 [7] Signac_1.0.0        Seurat_3.2.2        reticulate_1.16    
[10] purrr_0.3.4         data.table_1.13.2   cowplot_1.1.0      
[13] ggplot2_3.3.2       MOFA2_0.99.6       

loaded via a namespace (and not attached):
  [1] rappdirs_0.3.1              SnowballC_0.7.0            
  [3] rtracklayer_1.50.0          pbdZMQ_0.3-4               
  [5] GGally_2.0.0                tidyr_1.1.2                
  [7] bit64_4.0.5                 knitr_1.30                 
  [9] irlba_2.3.3                 DelayedArray_0.16.0        
 [11] rpart_4.1-15                RCurl_1.98-1.2             
 [13] AnnotationFilter_1.14.0     generics_0.0.2             
 [15] GenomicFeatures_1.42.0      RSQLite_2.2.1              
 [17] RANN_2.6.1                  future_1.20.1              
 [19] bit_4.0.4                   spatstat.data_1.4-3        
 [21] xml2_1.3.2                  httpuv_1.5.4               
 [23] SummarizedExperiment_1.20.0 assertthat_0.2.1           
 [25] xfun_0.18                   hms_0.5.3                  
 [27] evaluate_0.14               promises_1.1.1             
 [29] progress_1.2.2              readxl_1.3.1               
 [31] dbplyr_2.0.0                tmvnsim_1.0-2              
 [33] igraph_1.2.6                DBI_1.1.0                  
 [35] htmlwidgets_1.5.2           reshape_0.8.8              
 [37] stats4_4.0.3                ellipsis_0.3.1             
 [39] RSpectra_0.16-0             corrplot_0.84              
 [41] dplyr_1.0.2                 backports_1.1.10           
 [43] biomaRt_2.46.0              deldir_0.2-2               
 [45] MatrixGenerics_1.2.0        vctrs_0.3.4                
 [47] Biobase_2.50.0              Cairo_1.5-12.2             
 [49] ensembldb_2.14.0            ROCR_1.0-11                
 [51] abind_1.4-5                 withr_2.3.0                
 [53] BSgenome_1.58.0             checkmate_2.0.0            
 [55] sctransform_0.3.1           GenomicAlignments_1.26.0   
 [57] prettyunits_1.1.1           mnormt_2.0.2               
 [59] goftest_1.2-2               cluster_2.1.0              
 [61] IRdisplay_0.7.0             lazyeval_0.2.2             
 [63] crayon_1.3.4                labeling_0.3               
 [65] pkgconfig_2.0.3             GenomeInfoDb_1.26.0        
 [67] nlme_3.1-149                vipor_0.4.5                
 [69] ProtGenerics_1.22.0         nnet_7.3-14                
 [71] rlang_0.4.8                 globals_0.13.1             
 [73] lifecycle_0.2.0             miniUI_0.1.1.1             
 [75] BiocFileCache_1.14.0        rsvd_1.0.3                 
 [77] dichromat_2.0-0             cellranger_1.1.0           
 [79] ggrastr_0.2.1               polyclip_1.10-0            
 [81] matrixStats_0.57.0          lmtest_0.9-38              
 [83] graph_1.68.0                Matrix_1.2-18              
 [85] ggseqlogo_0.1               IRkernel_1.1.1.9000        
 [87] carData_3.0-4               Rhdf5lib_1.10.1            
 [89] zoo_1.8-8                   base64enc_0.1-3            
 [91] beeswarm_0.2.3              ggridges_0.5.2             
 [93] pheatmap_1.0.12             png_0.1-7                  
 [95] viridisLite_0.3.0           bitops_1.0-6               
 [97] KernSmooth_2.23-17          Biostrings_2.58.0          
 [99] blob_1.2.1                  stringr_1.4.0              
[101] qvalue_2.22.0               parallelly_1.21.0          
[103] jpeg_0.1-8.1                rstatix_0.6.0              
[105] S4Vectors_0.28.0            ggsignif_0.6.0             
[107] scales_1.1.1                memoise_1.1.0              
[109] plyr_1.8.6                  ica_1.0-2                  
[111] zlibbioc_1.36.0             compiler_4.0.3             
[113] RColorBrewer_1.1-2          fitdistrplus_1.1-1         
[115] Rsamtools_2.6.0             XVector_0.30.0             
[117] listenv_0.8.0               patchwork_1.0.1            
[119] pbapply_1.4-3               htmlTable_2.1.0            
[121] Formula_1.2-4               MASS_7.3-53                
[123] mgcv_1.8-33                 tidyselect_1.1.0           
[125] stringi_1.5.3               forcats_0.5.0              
[127] askpass_1.1                 latticeExtra_0.6-29        
[129] ggrepel_0.8.2               grid_4.0.3                 
[131] VariantAnnotation_1.36.0    fastmatch_1.1-0            
[133] tools_4.0.3                 future.apply_1.6.0         
[135] rio_0.5.16                  rstudioapi_0.11            
[137] uuid_0.1-4                  foreign_0.8-80             
[139] lsa_0.73.2                  gridExtra_2.3              
[141] farver_2.0.3                Rtsne_0.15                 
[143] digest_0.6.25               BiocManager_1.30.10        
[145] shiny_1.5.0                 Rcpp_1.0.5                 
[147] GenomicRanges_1.42.0        car_3.0-10                 
[149] broom_0.7.2                 later_1.1.0.1              
[151] RcppAnnoy_0.0.16            OrganismDbi_1.32.0         
[153] httr_1.4.2                  AnnotationDbi_1.52.0       
[155] biovizBase_1.38.0           colorspace_1.4-1           
[157] XML_3.99-0.5                tensor_1.5                 
[159] IRanges_2.24.0              splines_4.0.3              
[161] uwot_0.1.8                  RBGL_1.66.0                
[163] RcppRoll_0.3.0              spatstat.utils_1.17-0      
[165] plotly_4.9.2.1              xtable_1.8-4               
[167] jsonlite_1.7.1              spatstat_1.64-1            
[169] R6_2.4.1                    Hmisc_4.4-1                
[171] pillar_1.4.6                htmltools_0.5.0            
[173] mime_0.9                    glue_1.4.2                 
[175] fastmap_1.0.1               BiocParallel_1.24.0        
[177] codetools_0.2-16            lattice_0.20-41            
[179] tibble_3.0.4                curl_4.3                   
[181] ggbeeswarm_0.6.0            leiden_0.3.4               
[183] zip_2.1.1                   openxlsx_4.2.3             
[185] openssl_1.4.3               survival_3.2-7             
[187] repr_1.1.0                  munsell_0.5.0              
[189] rhdf5_2.32.4                GenomeInfoDbData_1.2.4     
[191] HDF5Array_1.16.1            haven_2.3.1                
[193] reshape2_1.4.4              gtable_0.3.0